


import os
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch

import numpy as np
from datasets import Dataset

from transformers.models.realm.configuration_realm import RealmConfig
from transformers.models.realm.retrieval_realm import _REALM_BLOCK_RECORDS_FILENAME, RealmRetriever
from transformers.models.realm.tokenization_realm import VOCAB_FILES_NAMES, RealmTokenizer







class 							UpperCamelCase__ (						__magic_name__ ):

					def 	UpperCAmelCase__							(  self							: int							):






										'''simple docstring'''






										lowercase_					=      tempfile.mkdtemp()
										lowercase_					=      5

										# Realm tok
										lowercase_					=      [
										    """[UNK]""",
										    """[CLS]""",
										    """[SEP]""",
										    """[PAD]""",
										    """[MASK]""",
										    """test""",
										    """question""",
										    """this""",
										    """is""",
										    """the""",
										    """first""",
										    """second""",
										    """third""",
										    """fourth""",
										    """fifth""",
										    """record""",
										    """want""",
										    """##want""",
										    """##ed""",
										    """wa""",
										    """un""",
										    """runn""",
										    """##ing""",
										    """,""",
										    """low""",
										    """lowest""",
										]
										lowercase_					=      os.path.join(self.tmpdirname				,       """realm_tokenizer"""							)
										os.makedirs(lowercase_				,       exist_ok=lowercase_							)
										lowercase_					=      os.path.join(lowercase_				,       VOCAB_FILES_NAMES["""vocab_file"""]							)
										with open(self.vocab_file				,       """w"""				,       encoding="""utf-8"""							) as vocab_writer:
															vocab_writer.write("""""".join([x + """\n""" for x in vocab_tokens]							)							)

										lowercase_					=      os.path.join(self.tmpdirname				,       """realm_block_records"""							)
										os.makedirs(lowercase_				,       exist_ok=lowercase_							)

					def 	UpperCAmelCase__							(  self							: Tuple							):






										'''simple docstring'''






										return RealmTokenizer.from_pretrained(os.path.join(self.tmpdirname				,       """realm_tokenizer"""							)							)

					def 	UpperCAmelCase__							(  self							: int							):






										'''simple docstring'''






										shutil.rmtree(self.tmpdirname							)

					def 	UpperCAmelCase__							(  self							: Optional[int]							):






										'''simple docstring'''






										lowercase_					=      RealmConfig(num_block_records=self.num_block_records							)
										return config

					def 	UpperCAmelCase__							(  self							: Union[str, Any]							):






										'''simple docstring'''






										lowercase_					=      Dataset.from_dict(
										    {
										        """id""": ["""0""", """1"""],
										        """question""": ["""foo""", """bar"""],
										        """answers""": [["""Foo""", """Bar"""], ["""Bar"""]],
										    }							)
										return dataset

					def 	UpperCAmelCase__							(  self							: str							):






										'''simple docstring'''






										lowercase_					=      np.array(
										    [
										        b"""This is the first record""",
										        b"""This is the second record""",
										        b"""This is the third record""",
										        b"""This is the fourth record""",
										        b"""This is the fifth record""",
										        b"""This is a longer longer longer record""",
										    ]				,       dtype=lowercase_				,       )
										return block_records

					def 	UpperCAmelCase__							(  self							: Optional[Any]							):






										'''simple docstring'''






										lowercase_					=      RealmRetriever(
										    block_records=self.get_dummy_block_records()				,       tokenizer=self.get_tokenizer()				,       )
										return retriever

					def 	UpperCAmelCase__							(  self							: str							):






										'''simple docstring'''






										lowercase_					=      self.get_config()
										lowercase_					=      self.get_dummy_retriever()
										lowercase_					=      retriever.tokenizer

										lowercase_					=      np.array([0, 3]				,       dtype="""long"""							)
										lowercase_					=      tokenizer(["""Test question"""]							).input_ids
										lowercase_					=      tokenizer(
										    ["""the fourth"""]				,       add_special_tokens=lowercase_				,       return_token_type_ids=lowercase_				,       return_attention_mask=lowercase_				,       ).input_ids
										lowercase_					=      config.reader_seq_len

										lowercase_				,       lowercase_				,       lowercase_				,       lowercase_					=      retriever(
										    lowercase_				,       lowercase_				,       answer_ids=lowercase_				,       max_length=lowercase_				,       return_tensors="""np"""							)

										self.assertEqual(len(lowercase_							)				,       2							)
										self.assertEqual(len(lowercase_							)				,       2							)
										self.assertEqual(len(lowercase_							)				,       2							)
										self.assertEqual(concat_inputs.input_ids.shape				,       (2, 10)							)
										self.assertEqual(concat_inputs.attention_mask.shape				,       (2, 10)							)
										self.assertEqual(concat_inputs.token_type_ids.shape				,       (2, 10)							)
										self.assertEqual(concat_inputs.special_tokens_mask.shape				,       (2, 10)							)
										self.assertEqual(
										    tokenizer.convert_ids_to_tokens(concat_inputs.input_ids[0]							)				,       ["""[CLS]""", """test""", """question""", """[SEP]""", """this""", """is""", """the""", """first""", """record""", """[SEP]"""]				,       )
										self.assertEqual(
										    tokenizer.convert_ids_to_tokens(concat_inputs.input_ids[1]							)				,       ["""[CLS]""", """test""", """question""", """[SEP]""", """this""", """is""", """the""", """fourth""", """record""", """[SEP]"""]				,       )

					def 	UpperCAmelCase__							(  self							: Union[str, Any]							):






										'''simple docstring'''






										lowercase_					=      self.get_config()
										lowercase_					=      self.get_dummy_retriever()
										lowercase_					=      retriever.tokenizer

										lowercase_					=      np.array([0, 3, 5]				,       dtype="""long"""							)
										lowercase_					=      tokenizer(["""Test question"""]							).input_ids
										lowercase_					=      tokenizer(
										    ["""the fourth""", """longer longer"""]				,       add_special_tokens=lowercase_				,       return_token_type_ids=lowercase_				,       return_attention_mask=lowercase_				,       ).input_ids
										lowercase_					=      config.reader_seq_len

										lowercase_				,       lowercase_				,       lowercase_				,       lowercase_					=      retriever(
										    lowercase_				,       lowercase_				,       answer_ids=lowercase_				,       max_length=lowercase_				,       return_tensors="""np"""							)

										self.assertEqual([False, True, True]				,       lowercase_							)
										self.assertEqual([[-1, -1, -1], [6, -1, -1], [6, 7, 8]]				,       lowercase_							)
										self.assertEqual([[-1, -1, -1], [7, -1, -1], [7, 8, 9]]				,       lowercase_							)







					def 	UpperCAmelCase__							(  self							: int							):






										'''simple docstring'''






										lowercase_					=      self.get_dummy_retriever()
										retriever.save_pretrained(os.path.join(self.tmpdirname				,       """realm_block_records"""							)							)

										# Test local path
										lowercase_					=      retriever.from_pretrained(os.path.join(self.tmpdirname				,       """realm_block_records"""							)							)
										self.assertEqual(retriever.block_records[0]				,       b"""This is the first record"""							)

										# Test mocked remote path
										with patch("""transformers.models.realm.retrieval_realm.hf_hub_download"""							) as mock_hf_hub_download:
															lowercase_					=      os.path.join(
															    os.path.join(self.tmpdirname				,       """realm_block_records"""							)				,       _REALM_BLOCK_RECORDS_FILENAME							)
															lowercase_					=      RealmRetriever.from_pretrained("""google/realm-cc-news-pretrained-openqa"""							)

										self.assertEqual(retriever.block_records[0]				,       b"""This is the first record"""							)



from __future__ import annotations


def 				lowerCAmelCase__       (			a__    ,     a__ = None    ,     a__ = None    ,     a__ = False    ,     )      ->tuple[int, float, str]:




  '''simple docstring'''

  _UpperCamelCase           =    cipher_alphabet or [chr(a__ ) for i in range(97    ,     123 )]

  # If the argument is None or the user provided an empty dictionary
  if not frequencies_dict:
    # Frequencies of letters in the english language (how much they show up)
    _UpperCamelCase           =    {
        "a": 0.08497,
        "b": 0.01492,
        "c": 0.02202,
        "d": 0.04253,
        "e": 0.11162,
        "f": 0.02228,
        "g": 0.02015,
        "h": 0.06094,
        "i": 0.07546,
        "j": 0.00153,
        "k": 0.01292,
        "l": 0.04025,
        "m": 0.02406,
        "n": 0.06749,
        "o": 0.07507,
        "p": 0.01929,
        "q": 0.00095,
        "r": 0.07587,
        "s": 0.06327,
        "t": 0.09356,
        "u": 0.02758,
        "v": 0.00978,
        "w": 0.02560,
        "x": 0.00150,
        "y": 0.01994,
        "z": 0.00077,
    }
  else:
    # Custom frequencies dictionary
    _UpperCamelCase           =    frequencies_dict

  if not case_sensitive:
    _UpperCamelCase           =    ciphertext.lower()

  # Chi squared statistic values
  _UpperCamelCase           =    {}

  # cycle through all of the shifts
  for shift in range(len(a__ ) ):
    _UpperCamelCase           =    ""

    # decrypt the message with the shift
    for letter in ciphertext:
      try:
        # Try to index the letter in the alphabet
        _UpperCamelCase           =    (alphabet_letters.index(letter.lower() ) - shift) % len(
            a__ )
        decrypted_with_shift += (
            alphabet_letters[new_key].upper()
            if case_sensitive and letter.isupper()
            else alphabet_letters[new_key]
        )
      except ValueError:
        # Append the character if it isn't in the alphabet
        decrypted_with_shift += letter

    _UpperCamelCase           =    0.0

    # Loop through each letter in the decoded message with the shift
    for letter in decrypted_with_shift:
      if case_sensitive:
        _UpperCamelCase           =    letter.lower()
        if letter in frequencies:
          # Get the amount of times the letter occurs in the message
          _UpperCamelCase           =    decrypted_with_shift.lower().count(a__ )

          # Get the excepcted amount of times the letter should appear based
          # on letter frequencies
          _UpperCamelCase           =    frequencies[letter] * occurrences

          # Complete the chi squared statistic formula
          _UpperCamelCase           =    ((occurrences - expected) ** 2) / expected

          # Add the margin of error to the total chi squared statistic
          chi_squared_statistic += chi_letter_value
      else:
        if letter.lower() in frequencies:
          # Get the amount of times the letter occurs in the message
          _UpperCamelCase           =    decrypted_with_shift.count(a__ )

          # Get the excepcted amount of times the letter should appear based
          # on letter frequencies
          _UpperCamelCase           =    frequencies[letter] * occurrences

          # Complete the chi squared statistic formula
          _UpperCamelCase           =    ((occurrences - expected) ** 2) / expected

          # Add the margin of error to the total chi squared statistic
          chi_squared_statistic += chi_letter_value

        # Add the data to the chi_squared_statistic_values dictionary
    _UpperCamelCase           =    (
        chi_squared_statistic,
        decrypted_with_shift,
    )

  # Get the most likely cipher by finding the cipher with the smallest chi squared
  # statistic
  def chi_squared_statistic_values_sorting_key(a__ ) -> tuple[float, str]:
    return chi_squared_statistic_values[key]

  _UpperCamelCase           =    min(
      a__    ,     key=a__    ,     )

  # Get all the data from the most likely cipher (key, decoded message)
  (
      (
      _UpperCamelCase
  )      ,						(
      _UpperCamelCase
  )      ,						
  )           =    chi_squared_statistic_values[most_likely_cipher]

  # Return the data on the most likely shift
  return (
      most_likely_cipher,
      most_likely_cipher_chi_squared_value,
      decoded_most_likely_cipher,
  )




